32 citations · 97 across the 11 of their papers we have counts for
11 papers
Konstruktor: A Strong Baseline for Simple Knowledge Graph Question Answering
Maria Lysyuk, Mikhail Salnikov, Pavel Braslavski +1
While being one of the most popular question types, simple questions such as "Who is the author of Cinderella?", are still not completely solved. Surprisingly, even the most powerf…
KazQAD: Kazakh Open-Domain Question Answering Dataset
Rustem Yeshpanov, Pavel Efimov, Leonid Boytsov +2
We introduce KazQAD -- a Kazakh open-domain question answering (ODQA) dataset -- that can be used in both reading comprehension and full ODQA settings, as well as for information r…
Answer Candidate Type Selection: Text-to-Text Language Model for Closed Book Question Answering Meets Knowledge Graphs
Mikhail Salnikov, Maria Lysyuk, Pavel Braslavski +3
Pre-trained Text-to-Text Language Models (LMs), such as T5 or BART yield promising results in the Knowledge Graph Question Answering (KGQA) task. However, the capacity of the model…
Large Language Models Meet Knowledge Graphs to Answer Factoid Questions
Mikhail Salnikov, Hai Le, Prateek Rajput +4
Recently, it has been shown that the incorporation of structured knowledge into Large Language Models significantly improves the results for a variety of NLP tasks. In this paper,…
NEREL-BIO: A Dataset of Biomedical Abstracts Annotated with Nested Named Entities
Natalia Loukachevitch, Suresh Manandhar, Elina Baral +5
This paper describes NEREL-BIO -- an annotation scheme and corpus of PubMed abstracts in Russian and smaller number of abstracts in English. NEREL-BIO extends the general domain da…
The Impact of Cross-Lingual Adjustment of Contextual Word Representations on Zero-Shot Transfer
Pavel Efimov, Leonid Boytsov, Elena Arslanova +1
Large multilingual language models such as mBERT or XLM-R enable zero-shot cross-lingual transfer in various IR and NLP tasks. Cao et al. (2020) proposed a data- and compute-effici…
NEREL: A Russian Dataset with Nested Named Entities, Relations and Events
Natalia Loukachevitch, Ekaterina Artemova, Tatiana Batura +6
In this paper, we present NEREL, a Russian dataset for named entity recognition and relation extraction. NEREL is significantly larger than existing Russian datasets: to date it co…
A Systematic Evaluation of Transfer Learning and Pseudo-labeling with BERT-based Ranking Models
Iurii Mokrii, Leonid Boytsov, Pavel Braslavski
Due to high annotation costs making the best use of existing human-created training data is an important research direction. We, therefore, carry out a systematic evaluation of tra…
RuBQ: A Russian Dataset for Question Answering over Wikidata
Vladislav Korablinov, Pavel Braslavski
The paper presents RuBQ, the first Russian knowledge base question answering (KBQA) dataset. The high-quality dataset consists of 1,500 Russian questions of varying complexity, the…
SberQuAD -- Russian Reading Comprehension Dataset: Description and Analysis
Pavel Efimov, Andrey Chertok, Leonid Boytsov +1
SberQuAD -- a large scale analog of Stanford SQuAD in the Russian language - is a valuable resource that has not been properly presented to the scientific community. We fill this g…
Personal Names Popularity Estimation and its Application to Record Linkage
Ksenia Zhagorina, Pavel Braslavski, Vladimir Gusev
This study deals with a fairly simply formulated problem -- how to estimate the number of people bearing the same full name in a large population. Estimation of name popularity can…